Uncalibrated visual servo for unmanned aerial manipulation

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper addresses the problem of autonomous servoing an unmanned redundant aerial manipulator using computer vision. The overactuation of the system is exploited by means of a hierarchical control law, which allows to prioritize several tasks during flight. We propose a safety-related primary task to avoid possible collisions. As a secondary task, we present an uncalibrated image-based visual servo strategy to drive the arm end-effector to a desired position and orientation by using a camera attached to it. In contrast to the previous visual servo approaches, a known value of camera focal length is not strictly required. To further improve flight behavior, we hierarchically add one task to reduce dynamic effects by vertically aligning the arm center of gravity to the multirotor gravitational vector, and another one that keeps the arm close to a desired configuration of high manipulability and avoiding arm joint limits. The performance of the hierarchical control law, with and without activation of each of the tasks, is shown in simulations and in real experiments confirming the viability of such prioritized control scheme for aerial manipulation.Peer ReviewedPostprint (author's final draft

Visual guidance of unmanned aerial manipulators

The ability to fly has greatly expanded the possibilities for robots to perform surveillance, inspection or map generation tasks. Yet it was only in recent years that research in aerial robotics was mature enough to allow active interactions with the environment. The robots responsible for these interactions are called aerial manipulators and usually combine a multirotor platform and one or more robotic arms. The main objective of this thesis is to formalize the concept of aerial manipulator and present guidance methods, using visual information, to provide them with autonomous functionalities. A key competence to control an aerial manipulator is the ability to localize it in the environment. Traditionally, this localization has required external infrastructure of sensors (e.g., GPS or IR cameras), restricting the real applications. Furthermore, localization methods with on-board sensors, exported from other robotics fields such as simultaneous localization and mapping (SLAM), require large computational units becoming a handicap in vehicles where size, load, and power consumption are important restrictions. In this regard, this thesis proposes a method to estimate the state of the vehicle (i.e., position, orientation, velocity and acceleration) by means of on-board, low-cost, light-weight and high-rate sensors. With the physical complexity of these robots, it is required to use advanced control techniques during navigation. Thanks to their redundancy on degrees-of-freedom, they offer the possibility to accomplish not only with mobility requirements but with other tasks simultaneously and hierarchically, prioritizing them depending on their impact to the overall mission success. In this work we present such control laws and define a number of these tasks to drive the vehicle using visual information, guarantee the robot integrity during flight, and improve the platform stability or increase arm operability. The main contributions of this research work are threefold: (1) Present a localization technique to allow autonomous navigation, this method is specifically designed for aerial platforms with size, load and computational burden restrictions. (2) Obtain control commands to drive the vehicle using visual information (visual servo). (3) Integrate the visual servo commands into a hierarchical control law by exploiting the redundancy of the robot to accomplish secondary tasks during flight. These tasks are specific for aerial manipulators and they are also provided. All the techniques presented in this document have been validated throughout extensive experimentation with real robotic platforms.La capacitat de volar ha incrementat molt les possibilitats dels robots per a realitzar tasques de vigilància, inspecció o generació de mapes. Tot i això, no és fins fa pocs anys que la recerca en robòtica aèria ha estat prou madura com per començar a permetre interaccions amb l’entorn d’una manera activa. Els robots per a fer-ho s’anomenen manipuladors aeris i habitualment combinen una plataforma multirotor i un braç robòtic. L’objectiu d’aquesta tesi és formalitzar el concepte de manipulador aeri i presentar mètodes de guiatge, utilitzant informació visual, per dotar d’autonomia aquest tipus de vehicles. Una competència clau per controlar un manipulador aeri és la capacitat de localitzar-se en l’entorn. Tradicionalment aquesta localització ha requerit d’infraestructura sensorial externa (GPS, càmeres IR, etc.), limitant així les aplicacions reals. Pel contrari, sistemes de localització exportats d’altres camps de la robòtica basats en sensors a bord, com per exemple mètodes de localització i mapejat simultànis (SLAM), requereixen de gran capacitat de còmput, característica que penalitza molt en vehicles on la mida, pes i consum elèctric son grans restriccions. En aquest sentit, aquesta tesi proposa un mètode d’estimació d’estat del robot (posició, velocitat, orientació i acceleració) a partir de sensors instal·lats a bord, de baix cost, baix consum computacional i que proporcionen mesures a alta freqüència. Degut a la complexitat física d’aquests robots, és necessari l’ús de tècniques de control avançades. Gràcies a la seva redundància de graus de llibertat, aquests robots ens ofereixen la possibilitat de complir amb els requeriments de mobilitat i, simultàniament, realitzar tasques de manera jeràrquica, ordenant-les segons l’impacte en l’acompliment de la missió. En aquest treball es presenten aquestes lleis de control, juntament amb la descripció de tasques per tal de guiar visualment el vehicle, garantir la integritat del robot durant el vol, millorar de l’estabilitat del vehicle o augmentar la manipulabilitat del braç. Aquesta tesi es centra en tres aspectes fonamentals: (1) Presentar una tècnica de localització per dotar d’autonomia el robot. Aquest mètode està especialment dissenyat per a plataformes amb restriccions de capacitat computacional, mida i pes. (2) Obtenir les comandes de control necessàries per guiar el vehicle a partir d’informació visual. (3) Integrar aquestes accions dins una estructura de control jeràrquica utilitzant la redundància del robot per complir altres tasques durant el vol. Aquestes tasques son específiques per a manipuladors aeris i també es defineixen en aquest document. Totes les tècniques presentades en aquesta tesi han estat avaluades de manera experimental amb plataformes robòtiques real

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

Autonomous Visual Servo Robotic Capture of Non-cooperative Target

This doctoral research develops and validates experimentally a vision-based control scheme for the autonomous capture of a non-cooperative target by robotic manipulators for active space debris removal and on-orbit servicing. It is focused on the final capture stage by robotic manipulators after the orbital rendezvous and proximity maneuver being completed. Two challenges have been identified and investigated in this stage: the dynamic estimation of the non-cooperative target and the autonomous visual servo robotic control. First, an integrated algorithm of photogrammetry and extended Kalman filter is proposed for the dynamic estimation of the non-cooperative target because it is unknown in advance. To improve the stability and precision of the algorithm, the extended Kalman filter is enhanced by dynamically correcting the distribution of the process noise of the filter. Second, the concept of incremental kinematic control is proposed to avoid the multiple solutions in solving the inverse kinematics of robotic manipulators. The proposed target motion estimation and visual servo control algorithms are validated experimentally by a custom built visual servo manipulator-target system. Electronic hardware for the robotic manipulator and computer software for the visual servo are custom designed and developed. The experimental results demonstrate the effectiveness and advantages of the proposed vision-based robotic control for the autonomous capture of a non-cooperative target. Furthermore, a preliminary study is conducted for future extension of the robotic control with consideration of flexible joints

A Multi-Sensorial Hybrid Control for Robotic Manipulation in Human-Robot Workspaces

Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach

Adaptive Neuro-Filtering Based Visual Servo Control of a Robotic Manipulator

This paper focuses on the solutions to flexibly regulate robotic by vision. A new visual servoing technique based on the Kalman filtering (KF) combined neural network (NN) is developed, which need not have any calibration parameters of robotic system. The statistic knowledge of the system noise and observation noise are first given by Gaussian white noise sequences, the nonlinear mapping between robotic vision and motor spaces are then on-line identified using standard Kalman recursive equations. In real robotic workshops, the perfect statistic knowledge of the noise is not easy to be derived, thus an adaptive neuro-filtering approach based on KF is also studied for mapping on-line estimation in this paper. The Kalman recursive equations are improved by a feedforward NN, in which the neural estimator dynamic adjusts its weights to minimize estimation error of robotic vision-motor mapping, without the knowledge of noise variances. Finally, the proposed visual servoing based on adaptive neuro-filtering has been successfully implemented in robotic pose regulation, and the experimental results demonstrate its validity and practicality for a six-degree-of-freedom (DOF) robotic system which the hand-eye without calibrated

Experimental study on visual servo control of robots.

Lam Kin Kwan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 67-70).Abstracts in English and Chinese.Chapter 1. --- Introduction --- p.1Chapter 1.1 --- Visual Servoing --- p.1Chapter 1.1.1 --- System Architectures --- p.2Chapter 1.1.1.1 --- Position-based Visual Servoing --- p.2Chapter 1.1.1.2 --- Image-based Visual Servoing --- p.3Chapter 1.1.2 --- Camera Configurations --- p.4Chapter 1.2 --- Problem Definition --- p.5Chapter 1.3 --- Related Work --- p.6Chapter 1.4 --- Contribution of This Work --- p.9Chapter 1.5 --- Organization of This Thesis --- p.10Chapter 2. --- System Modeling --- p.11Chapter 2.1 --- Coordinate Frames --- p.11Chapter 2.2 --- System Kinematics --- p.13Chapter 2.3 --- System Dynamics --- p.14Chapter 2.4 --- Camera Model --- p.15Chapter 2.4.1 --- Eye-in-hand Configuration --- p.18Chapter 2.4.2 --- Eye-and-hand Configuration --- p.21Chapter 3. --- Adaptive Visual Servoing Control --- p.24Chapter 3.1 --- Controller Design --- p.24Chapter 3.2 --- Parameter Estimation --- p.27Chapter 3.3 --- Stability Analysis --- p.30Chapter 4. --- Experimental Studies --- p.34Chapter 4.1 --- Experimental Setup --- p.34Chapter 4.1.1 --- Hardware Setup --- p.34Chapter 4.1.2 --- Image Pattern Recognition --- p.35Chapter 4.1.3 --- Experimental Task --- p.36Chapter 4.2 --- Control Performance with Different Proportional Gains and Derivative Gains --- p.39Chapter 4.3 --- Control Performance with Different Adaptive Gains --- p.41Chapter 4.4 --- Gravity Compensator --- p.50Chapter 4.5 --- Control Performance with Previous Image Positions --- p.51Chapter 4.6 --- Kinematic Controller --- p.56Chapter 5. --- Conclusions --- p.61Chapter 5.1 --- Conclusions --- p.61Chapter 5.2 --- Future Work --- p.62Appendix --- p.63Bibliography --- p.6

Design of an Anthropomorphic, Compliant, and Lightweight Dual Arm for Aerial Manipulation

This paper presents an anthropomorphic, compliant and lightweight dual arm manipulator designed and developed for aerial manipulation applications with multi-rotor platforms. Each arm provides four degrees of freedom in a human-like kinematic configuration for end effector positioning: shoulder pitch, roll and yaw, and elbow pitch. The dual arm, weighting 1.3 kg in total, employs smart servo actuators and a customized and carefully designed aluminum frame structure manufactured by laser cut. The proposed design reduces the manufacturing cost as no computer numerical control machined part is used. Mechanical joint compliance is provided in all the joints, introducing a compact spring-lever transmission mechanism between the servo shaft and the links, integrating a potentiometer for measuring the deflection of the joints. The servo actuators are partially or fully isolated against impacts and overloads thanks to the ange bearings attached to the frame structure that support the rotation of the links and the deflection of the joints. This simple mechanism increases the robustness of the arms and safety in the physical interactions between the aerial robot and the environment. The developed manipulator has been validated through different experiments in fixed base test-bench and in outdoor flight tests.Unión Europea H2020-ICT-2014- 644271Ministerio de Economía y Competitividad DPI2015-71524-RMinisterio de Economía y Competitividad DPI2017-89790-